Currently, video compression is used in numerous applications, such as in professional applications but also oriented towards consumer applications.
Video compression is particularly used in applications of the telephony or videotelephony type, or also for audio data transmitted and exchanged between several correspondents, while simultaneously sending data of the video type. In such applications, the passband of the communication channels through which the video data are transmitted remains very limited, taking the considerable volume of the video data to be transmitted into account so as to have an acceptable quality of the images constituting the encoded video signal. It is thus necessary to make use of video compression standards adapted to small passbands, particularly to the video compression standard H.263 which is particularly dedicated to the encoding of video signals of a small format allowing generation of video signals encoded in several tens of kilobits per second.
Within the scope of applications of the telephony or videotelephony type, the video signals are transmitted through channels which are often perturbed, either because of the saturation of the passband of said channels or by transmission breaks, notably during wireless transmission, which perturbations involve loss of data in the transmitted video signals which are received by the decoder. In order to limit the effects of these perturbations, the H.263 standard provides protection of the video data constituting each image of the video signal at the level of the encoder before transmission through the transmission channels. To this end, this standard suggests that each image is cut up into slices which are encoded independently of each other. In this way, a loss of data occurring in an encoded image slice, referred to as current image, does not affect the other slices of said current image, which slices can be decoded under certain conditions. The decoding of other slices of said current image is only possible if the contents of its image header have not been lost.
The European patent having reference EP1094672 describes a method that, under certain conditions, allows to decode a current image (or only some slices of a current image) that has been lost. Indeed, this method allows in certain cases to retrieve coding parameters useful for the decoding of the current image that would have been present in the most picture header.
This known method benefits from the fact that the video standard H.263 proposes that each encoded image comprises an image header and can be cut up into slices comprising a slice header, each slice header comprising an identifier field to be identified. The identifier fields, named GFID in the syntax of this standard, comply with encoding rules defined by the following rules: the identifier fields are identical for the slices of one and the same encoded image, the identity of the image headers of a current and a preceding encoded image involves the identity of identifier fields of these two images, a change in the image header of a current encoded image with respect to that of a preceding encoded image involves the change of identifier fields of said current image.
At the decoding, if identifier fields of previous and current pictures are different, it is possible to deduce that picture headers have changed, i.e. fields composing said picture headers have changed, but it Is not possible to know which fields in particular have changed. While respecting the standard H.263, this method proposes to define additional coding rules of the GFID field to be allowed to determine when decoding which fields have changed in particular in the picture header, and to deduce the new value of these fields to be used for the current picture.
This known method is subject to limitations.
First, when identifier fields associated to the previous and current pictures are different, this known method allows to identify the change of only one field at a time in picture headers. Thus, if many fields associated to the picture headers associated to the previous and current pictures have changed, only the field considered having the highest priority will be detected y this method, and its value for the current picture will be deducted. This method that not allows to detect that many fields have changed in picture headers. As a consequence, the non-detected fields may disturb the decoding of the current picture.
Secondly, when decoding, this method proposes that the identifier field GFID(n) associated to the current picture is deducted by means of a binary operation from the identifier field GFID(n−1) associated to the previous picture, depending of the change of a set of fields having increasing priorities. The value of the identifier field GFID(n) is then obtained relatively to the identifier field GFID(n−1). When many pictures been lost, for example (n−) pictures lost, this method does not work since at the decoding the field GFID(n−1) is not available considering that the picture having rank (n−1) has been lost. A comparison between field GFID(n) and field GFID(n−i), i.e. with the identifier field associated to the last picture available, has no sense because the number of lost pictures is not known a-priori and that this pictures loss can not be planned.
Finally, when decoding, in view of determining y which available picture header the picture header of the current picture can be replaced by, a comparison is done between the identifier field GFID(n) of the current image and the identifier field GFID(n+1) of the next picture. This implies a delay equal to one picture in the decoding, which leads to a prejudice when decoding video whose visual analysis must be real-time.